DEEP BISPECTRAL IMAGE ANALYSIS FOR SPEECH-BASED CONVERSATIONAL EMOTIONAL CLIMATE RECOGNITION
Author:
Affiliation:
1. Khalifa University, United Arab Emirates
2. American University of Sharjah, United Arab Emirates
3. Khalifa University of Science and Technology, United Arab Emirates
Funder
Khalifa University of Science, Technology and Research
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3652037.3663887
Reference24 articles.
1. Ghada Alhussein, Mohanad Alkhodari, Ahsan Khandokher, and Leontios J Hadjileontiadis. 2022. Emotional Climate Recognition in Interactive Conversational Speech Using Deep Learning. In 2022 IEEE International Conference on Digital Health (ICDH). IEEE, 96–103.
2. G. Alhussein and L. Hadjileontiadis. 2022. Digital Health Technologies for Long-term Self-management of Osteoporosis: Systematic Review and Meta-analysis. JMIR mHealth and uHealth 10 4 (2022) e32557.
3. IEMOCAP: interactive emotional dyadic motion capture database
4. X. Cai, D. Dai, Z. Wu, X. Li, J. Li, and H. Meng. 2021. Emotion controllable speech synthesis using emotion-unlabeled dataset with the assistance of cross-domain speech emotion recognition. In ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 5734–5738.
5. E. Dejonckheere M. Mestdagh M. Houben I. Rutten L. Sels P. Kuppens and F. Tuerlinckx. 2019. Complex affect dynamics add limited information to the prediction of psychological well-being. Nature human behaviour 3 5 (2019) 478–491.
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